Graph-theoretical analysis identifies transient spatial states of resting-state dynamic functional network connectivity and reveals dysconnectivity in schizophrenia.

Long, Qunfang; Bhinge, Suchita; Calhoun, Vince D; Adali, Tülay

Long, Qunfang; Bhinge, Suchita; Calhoun, Vince D; Adali, Tülay.

Afiliação

Long Q; Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, 21250, USA. Electronic address: qunfang1@umbc.edu.
Bhinge S; Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, 21250, USA.
Calhoun VD; The Mind Research Network, Albuquerque, NM, 87131, USA; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, 87131, USA; Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute
Adali T; Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, 21250, USA.

J Neurosci Methods ; 350: 109039, 2021 02 15.

Article em En | MEDLINE | ID: mdl-33370561

Assuntos

Esquizofrenia; Encéfalo/diagnóstico por imagem; Mapeamento Encefálico; Humanos; Imageamento por Ressonância Magnética; Esquizofrenia/diagnóstico por imagem

Palavras-chave

Adaptively constrained independent vector analysis; Dynamic functional network connectivity; Dynamic study; Functional magnetic resonance imaging; Graph-theoretical analysis

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Esquizofrenia Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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